:: Library Catalog

Copertina

Salvato in:

Dettagli Bibliografici
Autori principali:	Zhuo, Hao, Yang, Yicheng, Peng, Kewen
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning Software Engineering
Accesso online:	https://arxiv.org/abs/2504.15439
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Software Engineering Principles for Fairer Systems: Experiments with GroupCART
di: Peng, Kewen, et al.
Pubblicazione: (2025)

Whence Is A Model Fair? Fixing Fairness Bugs via Propensity Score Matching
di: Peng, Kewen, et al.
Pubblicazione: (2025)

A Systematic Literature Review on the Use of Machine Learning in Software Engineering
di: Fred, Nyaga, et al.
Pubblicazione: (2024)

Large Language Models for Software Engineering: A Reproducibility Crisis
di: Siddiq, Mohammed Latif, et al.
Pubblicazione: (2025)

Code Graph Model (CGM): A Graph-Integrated Large Language Model for Repository-Level Software Engineering Tasks
di: Tao, Hongyuan, et al.
Pubblicazione: (2025)

Perspective of Software Engineering Researchers on Machine Learning Practices Regarding Research, Review, and Education
di: Mojica-Hanke, Anamaria, et al.
Pubblicazione: (2024)

IDE-Bench: Evaluating Large Language Models as IDE Agents on Real-World Software Engineering Tasks
di: Mateega, Spencer, et al.
Pubblicazione: (2026)

Foundation Model Engineering: Engineering Foundation Models Just as Engineering Software
di: Ran, Dezhi, et al.
Pubblicazione: (2024)

Agint: Agentic Graph Compilation for Software Engineering Agents
di: Chivukula, Abhi, et al.
Pubblicazione: (2025)

Breaking the Silence: the Threats of Using LLMs in Software Engineering
di: Sallou, June, et al.
Pubblicazione: (2023)

The Rise of AI Teammates in Software Engineering (SE) 3.0: How Autonomous Coding Agents Are Reshaping Software Engineering
di: Li, Hao, et al.
Pubblicazione: (2025)

Toward Explaining Large Language Models in Software Engineering Tasks
di: Vitale, Antonio, et al.
Pubblicazione: (2025)

Assessing the Use of AutoML for Data-Driven Software Engineering
di: Calefato, Fabio, et al.
Pubblicazione: (2023)

Bridging the Language Gap: An Empirical Study of Bindings for Open Source Machine Learning Libraries Across Software Package Ecosystems
di: Li, Hao, et al.
Pubblicazione: (2022)

On the Replicability and Reproducibility of Deep Learning in Software Engineering
di: Liu, Chao, et al.
Pubblicazione: (2020)

A systematic literature Review for Transformer-based Software Vulnerability detection
di: Naseer, Fiza, et al.
Pubblicazione: (2026)

SeaView: Software Engineering Agent Visual Interface for Enhanced Workflow
di: Bula, Timothy, et al.
Pubblicazione: (2025)

Cataloguing Hugging Face Models to Software Engineering Activities: Automation and Findings
di: González, Alexandra, et al.
Pubblicazione: (2025)

SWE-Arena: An Interactive Platform for Evaluating Foundation Models in Software Engineering
di: Zhao, Zhimin
Pubblicazione: (2025)

Programming with Pixels: Can Computer-Use Agents do Software Engineering?
di: Aggarwal, Pranjal, et al.
Pubblicazione: (2025)

Agentless: Demystifying LLM-based Software Engineering Agents
di: Xia, Chunqiu Steven, et al.
Pubblicazione: (2024)

Challenges and Paths Towards AI for Software Engineering
di: Gu, Alex, et al.
Pubblicazione: (2025)

More Rigorous Software Engineering Would Improve Reproducibility in Machine Learning Research
di: Wolter, Moritz, et al.
Pubblicazione: (2025)

Face It Yourselves: An LLM-Based Two-Stage Strategy to Localize Configuration Errors via Logs
di: Shan, Shiwen, et al.
Pubblicazione: (2024)

Engineering Resource-constrained Software Systems with DNN Components: a Concept-based Pruning Approach
di: Formica, Federico, et al.
Pubblicazione: (2026)

Should Code Models Learn Pedagogically? A Preliminary Evaluation of Curriculum Learning for Real-World Software Engineering Tasks
di: Khant, Kyi Shin, et al.
Pubblicazione: (2025)

Investigating Reproducibility in Deep Learning-Based Software Fault Prediction
di: Mukhtar, Adil, et al.
Pubblicazione: (2024)

SWE-Lancer: Can Frontier LLMs Earn $1 Million from Real-World Freelance Software Engineering?
di: Miserendino, Samuel, et al.
Pubblicazione: (2025)

Beyond C/C++: Probabilistic and LLM Methods for Next-Generation Software Reverse Engineering
di: Zhuo, Zhuo, et al.
Pubblicazione: (2025)

LLMs in Coding and their Impact on the Commercial Software Engineering Landscape
di: Belozerov, Vladislav, et al.
Pubblicazione: (2025)

Trojans in Large Language Models of Code: A Critical Review through a Trigger-Based Taxonomy
di: Hussain, Aftab, et al.
Pubblicazione: (2024)

Program Structure-aware Language Models: Targeted Software Testing beyond Textual Semantics
di: Tran, Khang, et al.
Pubblicazione: (2026)

Effort and Size Estimation in Software Projects with Large Language Model-based Intelligent Interfaces
di: Coelho Jr, Claudionor N., et al.
Pubblicazione: (2024)

Towards Refining Developer Questions using LLM-Based Named Entity Recognition for Developer Chatroom Conversations
di: Fathollahzadeh, Pouya, et al.
Pubblicazione: (2025)

ChatGPT Incorrectness Detection in Software Reviews
di: Tanzil, Minaoar Hossain, et al.
Pubblicazione: (2024)

EGSS: Entropy-guided Stepwise Scaling for Reliable Software Engineering
di: Mao, Chenhui, et al.
Pubblicazione: (2026)

A Machine Learning-Based Error Mitigation Approach For Reliable Software Development On IBM'S Quantum Computers
di: Muqeet, Asmar, et al.
Pubblicazione: (2024)

Building Specialized Software-Assistant ChatBot with Graph-Based Retrieval-Augmented Generation
di: Hilel, Mohammed, et al.
Pubblicazione: (2025)

Sentiment Analysis in Software Engineering: Evaluating Generative Pre-trained Transformers
di: Saifullah, KM Khalid, et al.
Pubblicazione: (2025)

LLM-Based Design Pattern Detection
di: Schindler, Christian, et al.
Pubblicazione: (2025)